Certain systems use high precision sensors to provide information regarding vector quantities (such as acceleration or rotation rate). In certain types of sensors, to accurately provide measurements along a vector, a sensor desirably provides zero-output when the system is not experiencing a measureable quantity. However, certain systems may provide output signals even when an inertial sensor is not experiencing actual motion. When an output signal is produced and no measurable quantity is experienced by the sensor, the magnitude of the output signal represents a bias error. Traditionally, sensors may be factory calibrated such that when a sensor is turned on, the sensor has no bias errors. However, it is difficult to model all the possible sources of bias error during a factory calibration. For example, possible sources of bias error may include temperature variation, power cycling, long-time storage, thermal or mechanical shock, magnetic sensitivities, acceleration sensitivity, and vibration rectification. Further, the maintenance of a zero bias error is only one of several desirable quantities. It is also desirable that the sensor have a low noise output such that a navigation algorithm is able to differentiate the true signal from background noise sources.